Transparency Notice: Performance tracking began on
Feb 10, 2026 (genesis date).
Positions entered on that date are initial seeds based on existing consensus at launch.
All picks from Feb 11, 2026 onward are
real-time tracked picks with verifiable entry dates and prices.
This is NOT backtesting — no hindsight bias. Every pick is recorded BEFORE we know the outcome.
Last tracked: -
Honest Performance Tracking Live
Every consensus pick is tracked as a virtual position. Results are reported honestly — wins AND losses.
TP: +8%, SL: -4%, Max hold: 14 days. Positions also close when consensus drops.
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Win Rate
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Portfolio Value
Started at $10,000
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Open Positions
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Closed Trades
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Avg Win
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Avg Loss
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Profit Factor
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Streak
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Avg Hold Days
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Total Return %
Portfolio Value Over Time
Auto-Diagnosis AI Analysis
Sector Performance
Algorithm Report Card
Exit Reason Breakdown
Open Positions -
Recent Closed Trades
Transparency Notice: The $200/day challenge started on
Feb 10, 2026.
Day 1 results use the genesis consensus snapshot. All subsequent days are
real-time picks selected each morning before market open.
Both modes (Consensus and ML-Enhanced) trade the same $5,000 capital with identical rules.
Results include ALL trades — winners and losers. No cherry-picking.
$200/Day
Can our algorithms consistently make $200/day from $5,000 capital?
Consensus Mode: Picks top 5 consensus stocks daily, allocates $1,000 each.
Pure algorithm agreement — no tweaks, no bias. Honest results.
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Days Tracked
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Total P&L
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Avg Daily Return
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$200 Target Hit Rate
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Trade Win Rate
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Peak P&L
Cumulative P&L
Latest Challenge Trades
Daily Results History
Transparency Notice: Self-learning insights are generated from
real closed positions only — never from backtests.
Lessons require a minimum of 5 closed trades before pattern detection activates.
Each lesson shows its detection date, confidence level, and supporting data.
ML-Enhanced mode in the $200/day challenge applies these lessons automatically.
Self-Learning Insights Auto-Detected
The system automatically analyzes closed positions to detect patterns, rank algorithms,
and suggest improvements. These lessons are applied to the ML-Enhanced challenge mode.
Important Disclaimer
This tool is for educational and research purposes only and does not constitute financial advice.
All investments involve risk, including the possible loss of principal. Past performance does not guarantee future results.
Consult a licensed financial adviser before making any investment decisions.